IT Expert System

Big data Hadoop Module

Overview

Big Data will help to create new career growth opportunities for job seekers and growth for entirely new categories of companies, such as those that aggregate and analyses industry data. Many of these will be companies that sit in the middle of large information flows where data about products and services, buyers and suppliers, consumer preferences and intent can be captured and analyzed. Forward-thinking leaders across sectors should begin aggressively to build their organizations’ Big Data capabilities.

Module 1: BigData courses include: R, Hadoop, Pig, Hive, HBase, Sqoop, Storm, Spark, MongoDB, Casandra, Sqoop, Mahout

Module 2: Database, Tableua, R, Python Programming, Numpy, Pandas, Linear Problem Solving, Forecasting, Statistics

Students are encouraged to combine module 1 & 2 for the better career success and build a strong knowledge base for the current market tools/technology.

Database Administration

Database Combo Course

Course Content

Learn how to implement ETL and machine learning algorithms using BIGDATA technologies

Key concepts:

Module 1: Big Data Use Cases with Hadoop Technology

Time: ~32 hours

BIG DATA Foundation
Database – overview, Oracle PL/SQL [OCP]
Data warehouse, ETL
Volume, Velocity, Verocity
Data Warehouse vs BIG DATA
BIG DATA – Use cases, OLAP vs OLTP

BIG DATA Programming

Hadoop Architecture
Linux Shell Scripting
Hadoop Map Reduce
Sqoop – Data import and export
Programming with:
PIG
Hive
Mahout
MySQL
HBASE
Zookeeper
Storm/Spark – Real-time Analytics
Java/Python - UDF (User Define Functions)
Theory topics are complemented by hands-on LAB+ E2E Project

Module 2: Data Driven Decision By Managers

Time: 32 hours

Database and Data Analysis
Database vs DataWare house vs Big Data
Managerial decisions based on data - Introduction
Product Valuation [NPV, DCF, FV, PV, WAAC]
Statistic Overview
Forecasting, and Projection Algorithm [R, Excel]
Classification, Clustering, Regression Algorithm
Descriptive and Visual Data Analysis [tableau]
Machine Learning [Python, R]
Linear Problem [LP]
Excel Solver
R Programming
Python Statistical Library [NumPy, SciPy, Panda, PyLab]
Theory topics are complemented by hands-on LAB
Project Work/Case Study: Real Industrial problem solution in a classroom setting